Customer analytics (a.k.a. customer data analytics) use predictive analytics and market segmentation to analyze customer data and behavior and make a key business decision.
Customer data analytics involves an analysis of buying habits like credit card purchases; personally identifiable information (PII) like name, address, email address, phone number, number of credit cards and offers on them; and lifestyle preferences like loyalty memberships, magazine subscriptions, etc. to create customer profiles, forecast their future spends, and deliver relevant, timely, and anticipated offers. Customer analytics provides factual data that can help businesses make key business decisions like the site selection for the expansion plan, stocks, direct marketing, strategizing promotion plans, and customer relationship management.
As customers have access to information at their fingertips anywhere, anytime, giving them the power to choose based on reviews, price, trends, etc., customer data analytics is becoming a necessity for businesses to thrive. The deeper understanding that a business has about the customers’ buying habits, lifestyle preferences, and spending patterns, the more customized and targeted will their offer be – increasing the chances of grabbing attention rather than alienating them.
Customer analytics has many advantages. Some of them are:
- Increase ROI: Customer data analytics enables businesses to contact the right customers with highly relevant and targeted offers, thereby increasing the response rates and customer loyalty.
- Decrease customer attrition: Customer analytics enables businesses to predict the customers who are more likely to switch and proactively develop targeted campaigns to retain them.
- Expansion plans: Customer data analytics can predict fertile locations for businesses by analyzing drive-time, customer profile, etc. and determine dollar value. Using machine learning and artificial intelligence, businesses can evaluate the future store locations and strategize expansion plans.
- Reduce marketing costs: Customer analytics can help reduce campaign costs by targeting campaigns to those customers who are more likely to respond.
At Algoscale, we combine behavioral analytics with machine learning and artificial intelligence to offer a 360-degree customer view or determine sentiment about products and services.
- Customer Behavior Analytics
- Customer Acquisition Analytics
- Customer Satisfaction Analysis
- Customer Lifetime Value (CLV) Modeling
- Business Expansion Forecast
- Customer Engagement Strategies